Predicting intensive care need in women with preeclampsia using machine learning – a pilot study

Camilla Edvinssona Division of Obstetrics and Gynecology, Department of Clinical Sciences Lund, Lund University, Lund, Sweden;b Division of Anaesthesia and Intensive Care, Department of Clinical Sciences Lund, Lund University, Lund, Sweden;c Department of Anaesthesia and Intensive Care, Helsingborg Hospital, Helsingborg, SwedenCorrespondence[email protected]
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Ola Björnssond Division of Mathematical Statistics, Centre for Mathematical Sciences, Lund University, Lund, Sweden;e Department of Energy Sciences, Faculty of Engineering, Lund University, Lund, SwedenView further author information

Lena Erlandssona Division of Obstetrics and Gynecology, Department of Clinical Sciences Lund, Lund University, Lund, SwedenView further author information

Stefan R. Hanssona Division of Obstetrics and Gynecology, Department of Clinical Sciences Lund, Lund University, Lund, Sweden;f Department of Obstetrics and Gynecology, Skåne University Hospital, Lund/Malmö, Sweden

https://orcid.org/0000-0002-7838-9074 View further author information

Predicting intensive care need in women with preeclampsia using machine learning – a pilot study

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Predicting intensive care need in women with preeclampsia using machine learning – a pilot study

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